Presently, technology exists and is in practice for monitoring traffic in cities and other locations. Traffic is monitored using cameras that may be mounted on buildings or similar structures, on airborne vehicles, or in space on satellites or other structures. Software is used with these cameras to allow monitoring of movement of individual vehicles in traffic. However, physical limitations of the cameras and logic limitations on the software limit the usefulness of this technology.
One problem for traffic monitoring systems is tall buildings. Buildings present obstructions to traffic, as do tunnels, bridges, and other significant structures. Even large trucks can provide obstructions for cameras, dependent upon the position of the camera. Traffic monitoring software will identify vehicles in view and tag them with a reference number. Relative to the view of the cameras, vehicles will pass behind an obstruction on one side of the obstruction and emerge from the other side. Most traffic monitoring software has no means for quickly matching the emerging vehicles with the vehicles that went behind the obstruction, but tag them with new reference numbers and then, later, the reference numbers may be interconnected manually or automatically. In either case, with respect to real time, the vehicles are ‘lost’ once they travel behind an obstruction. High frequency of ‘lost’ vehicles limit the usefulness of traffic monitoring systems and traffic monitoring systems that cannot properly account for vehicles that pass behind obstructions provide a high frequency of ‘lost’ vehicles.
Some traffic monitoring systems are slightly more advanced. These traffic monitoring systems will attempt to measure a vehicle frame and associate tags of vehicles passing behind obstructions based on order into the obstruction and order out, using vehicle frame measurements to verify and apply corrective changes to the logic. Unfortunately, other traffic influences can exist behind obstructions that significantly impair this logic. Specifically, parking garage exits and entrances, traffic lights, double-parked vehicles, construction, intersections and many other traffic influences greatly influence traffic flow behind obstructions and can cause improper association of vehicles, which becomes corrupt data.
Thus, a heretofore unaddressed need exists in the industry to address the aforementioned deficiencies and inadequacies.